Article: Integrating IoT and machine learning for scalable anomaly detection in smart city infrastructure Journal: International Journal of Critical Infrastructures (IJCIS) 2026 Vol.22 No.10 pp.1 - 16 Abstract: People all over the world can connect a lot of smart things to the internet of things (IoT). These tools can talk to other tools in the same family without any help from people. The internet of things (IoT) lets us get and look at a lot of data. Many good things could come from this. A lot of data is made when more things join the IoT. You might find strange things after reading this. It has a lot of different kinds of things. Standard ways to keep an eye on hacking threats need to handle and process different kinds of data in different ways. This might not work well for files that have a lot of different parts. But data from more than one kind of network gadget can hold more kinds of data. It will help you find strange things more quickly. Inderscience Publishers - linking academia, business and industry through research

Title: Integrating IoT and machine learning for scalable anomaly detection in smart city infrastructure

Authors: Jing Xu

Addresses: Police Tactical Department, Fujian Police College, Fuzhou, Fujian, 350007, China

Abstract: People all over the world can connect a lot of smart things to the internet of things (IoT). These tools can talk to other tools in the same family without any help from people. The internet of things (IoT) lets us get and look at a lot of data. Many good things could come from this. A lot of data is made when more things join the IoT. You might find strange things after reading this. It has a lot of different kinds of things. Standard ways to keep an eye on hacking threats need to handle and process different kinds of data in different ways. This might not work well for files that have a lot of different parts. But data from more than one kind of network gadget can hold more kinds of data. It will help you find strange things more quickly.

Keywords: data pre-processing; anomaly detection dataset; benchmarking models; evolution of anomaly detection techniques; internet of things; IoT.

DOI: 10.1504/IJCIS.2026.152499

International Journal of Critical Infrastructures, 2026 Vol.22 No.10, pp.1 - 16

Received: 28 Dec 2024
Accepted: 10 Feb 2025
Published online: 24 Mar 2026 *

Title: Integrating IoT and machine learning for scalable anomaly detection in smart city infrastructure

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